Search results for: unmanned arial vehicle(UAV)

Authors: Tong He, Long Chen, Irag Mantegh, Wen-Fang Xie

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This paper proposes an image-based obstacle avoidance and tracking target identification strategy in GPS-degraded or GPS-denied environment for an Unmanned Aerial Vehicle (UAV). The traditional force algorithm for obstacle avoidance could produce local minima area, in which UAV cannot get away obstacle effectively. In order to eliminate it, an artificial potential approach based on harmonic potential is proposed to guide the UAV to avoid the obstacle by using the vision system. And image-based visual servoing scheme (IBVS) has been adopted to implement the proposed obstacle avoidance approach. In IBVS, the pixel accuracy is a key factor to realize the obstacle avoidance. In this paper, the deep reinforcement learning framework has been applied by reducing pixel errors through constant interaction between the environment and the agent. In addition, the combination of OpenTLD and Tensorflow based on neural network is used to identify the type of tracking target. Numerical simulation in Matlab and ROS GAZEBO show the satisfactory result in target identification and obstacle avoidance.

Keywords: image-based visual servoing, obstacle avoidance, tracking target identification, deep reinforcement learning, artificial potential approach, neural network

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Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad

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System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc.  This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error   technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.

Keywords: fixed wing UAV, system identification, black box modeling, longitudinal dynamics, least square error

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Authors: Kevin Anderson, Sukhwinder Singh Sandhu, Nouh Anies, Shilpa Ravichandra, Steven Dobbs, Donald Edberg

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This paper presents the results of a Finite Element based vibration analysis of a solar powered Unmanned Aerial Vehicle (UAV). The purpose of this paper was to quantify the free vibration, forced vibration response due to differing point inputs in order to mimic the vibration induced by actuators (magnet in coil generators) used to aid in the flight of the UAV. A Fluid-Structure Interaction (FSI) study was performed in order to ascertain pertinent deigns stresses and deflections as well as aerodynamic parameters of the UAV airfoil. The 10 ft span airfoil is modeled using Mylar as the primary material. Results show that the free mode in bending is 4.8 Hz while the first forced bending mode is in the range of 16.2 to 16.7 Hz depending on the location of excitation. The free torsional bending mode is 28.3 Hz, and the first forced torsional mode is in the range of 26.4 to 27.8 Hz, depending on the location of excitation. The FSI results predict the coefficients of aerodynamic drag and lift of 0.0052 and 0.077, respectively, which matches hand-calculations used to validate the Finite Element based results. FSI based maximum von Mises stresses and deflections were found to be 0.282 MPa and 3.4 mm, respectively. Dynamic pressures on the airfoil range of 1.04 to 1.23 kPa corresponding to velocity magnitudes in the range of 22 to 66 m/s.

Keywords: ANSYS, finite element, FSI, UAV, vibrations

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Authors: Tapan Upadhyay, Aqib Siddiqui, Sameer Khan

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Railway crossing system in India is a manually operated level crossing system, either manned or unmanned. The main aim is to protect pedestrians and vehicles from colliding with trains, which pass at regular intervals, as India has the largest and busiest railway network. But because of human error and negligence, every year thousands of lives are lost due to accidents at railway crossings. To avoid this, we suggest a solution, by using Programmable Logical Controller (PLC) based automatic system, which will automatically control the barrier as well as roadblocks to stop people from crossing while security warning is given. Often people avoid security warning, and pass two-wheelers from beneath the barrier, while the train is at a distance away. This paper aims at reducing the fatality and accident rate by controlling barrier and roadblocks using sensors which sense the incoming train and vehicles and sends a signal to PLC. The PLC in return sends a signal to barrier and roadblocks. Once the train passes, the barrier and roadblocks retrieve back, and the passage is clear for vehicles and pedestrians to cross. PLC’s are used because they are very flexible, cost effective, space efficient, reduces complexity and minimises errors. Supervisory Control And Data Acquisition (SCADA) is used to monitor the functioning.

Keywords: level crossing, PLC, sensors, SCADA

Procedia PDF Downloads 393

Authors: Francois Defay

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Uses of Unmanned aerial vehicle (UAV) are increasing for many applicative cases. Long endurance UAVs are required for inspection or transportation in some deserted places. The global optimization of the efficiency is the aim of the works in ISAE-SUPAERO. From the propulsive part until the motor control, the global optimization can increase significantly the global efficiency. This paper deals with the global improvement of the efficiency of the electrical propulsion for the aerial vehicle. The application case of study is a small airplane of 2kg. A global modelization is presented in order to validate the electrical engine in a complete simulation from aerodynamics to battery. The classical control of the synchronous permanent drive is compared to the field-oriented control which is not yet applied for UAVs. The experimental results presented show an increase of more than 10 percent of the efficiency. A complete modelization and simulation based on Matlab/ Simulink are presented in this paper and compared to the experimental study. Finally this paper presents solutions to increase the endurance of the electrical aerial vehicle and provide models to optimize the global consumption for a specific mission. The next step is to use this model and the control to work with distributed propulsion which is the future for small distance plane.

Keywords: electrical propulsion, endurance, field-oriented control, UAV

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Authors: Ibrahim Makram Ibrahim Salib

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Agriculture plays an essential role in providing food for the world's population. It also offers numerous benefits to countries, including non-food products, transportation, and environmental balance. Precision agriculture, which employs advanced tools to monitor variability and manage inputs, can help achieve these benefits. The increasing demand for food security puts pressure on decision-makers to ensure sufficient food production worldwide. To support sustainable agriculture, unmanned aerial vehicles (UAVs) can be utilized to manage farms and increase yields. This paper aims to provide an understanding of UAV usage and its applications in agriculture. The objective is to review the various applications of UAVs in agriculture. Based on a comprehensive review of existing research, it was found that different sensors provide varying analyses for agriculture applications. Therefore, the purpose of the project must be determined before using UAV technology for better data quality and analysis. In conclusion, identifying a suitable sensor and UAV is crucial to gather accurate data and precise analysis when using UAVs in agriculture.

Keywords: agriculture land, agriculture land loss, Kabul city, urban land expansion, urbanization agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models drone, precision agriculture, farmer income

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Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

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Unmanned Surface Vehicles (USVs) are valuable due to their ability to perform dangerous and time-consuming tasks on the water. Object detection tasks are significant in these applications. However, inherent challenges, such as the complex distribution of obstacles, reflections from shore structures, water surface fog, etc., hinder the performance of object detection of USVs. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. MMW radar is complementary to vision sensors, providing robust environmental information. The radar 3D point cloud is transferred to 2D radar pseudo image to unify radar and vision information format by utilizing the point transformer. We propose a multi-source object detection network (RV-YOLOX )based on radar-vision fusion for inland waterways environment. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: inland waterways, YOLO, sensor fusion, self-attention

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Authors: Mirza Mohibulla Baig, Imil Hamda Imran, Tri Bagus Susilo, Sami El Ferik

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The paper deals with system identification and control a nonlinear model of semi-autonomous underwater vehicle (UUV). The input-output data is first generated using the experimental values of the model parameters and then this data is used to compute the estimated parameter values. In this study, we use the semi-autonomous UUV LAURS model, which is developed by the Sensors and Actuators Laboratory in University of Sao Paolo. We applied three methods to identify the parameters: integral method, which is a classical least square method, recursive least square, and weighted recursive least square. In this paper, we also apply three different inputs (step input, sine wave input and random input) to each identification method. After the identification stage, we investigate the control performance of yaw motion of nonlinear semi-autonomous Unmanned Underwater Vehicle (UUV) using feedback linearization-based controller. In addition, we compare the performance of the control with an integral and a non-integral part along with state feedback. Finally, disturbance rejection and resilience of the controller is tested. The results demonstrate the ability of the system to recover from such fault.

Keywords: system identification, underwater vehicle, integral method, recursive least square, weighted recursive least square, feedback linearization, integral error

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Authors: Slim Namouchi, Bruno Vallet, Imed Riadh Farah

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3D urban models provide powerful tools for decision making, urban planning, and smart city services. The accuracy of this 3D based systems is directly related to the quality of these models. Since manual large-scale modeling, such as cities or countries is highly time intensive and very expensive process, a fully automatic 3D building generation is needed. However, 3D modeling process result depends on the input data, the proprieties of the captured objects, and the required characteristics of the reconstructed 3D model. Nowadays, producing 3D real-world model is no longer a problem. Remotely sensed data had experienced a remarkable increase in the recent years, especially data acquired using unmanned aerial vehicles (UAV). While the scanning techniques are developing, the captured data amount and the resolution are getting bigger and more precise. This paper presents a literature review, which aims to identify different methods of automatic 3D buildings extractions either from LiDAR or the combination of LiDAR and satellite or aerial images. Then, we present open source technologies, and data models (e.g., CityGML, PostGIS, Cesiumjs) used to integrate these models in geospatial base layers for smart city services.

Keywords: CityGML, LiDAR, remote sensing, SIG, Smart City, 3D urban modeling

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Authors: Xinhuang Wu, Yousef Sardahi

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A hybrid and optimal multi-loop control structure combining linear and nonlinear control algorithms are introduced in this paper to regulate the position of a quadcopter unmanned aerial vehicle (UAV) driven by four brushless DC motors. To this end, a nonlinear mathematical model of the UAV is derived and then linearized around one of its operating points. Using the nonlinear version of the model, a sliding mode control is used to derive the control laws of the motor thrust forces required to drive the UAV to a certain position. The linear model is used to design two controllers, XG-controller and YG-controller, responsible for calculating the required roll and pitch to maneuver the vehicle to the desired X and Y position. Three attitude controllers are designed to calculate the desired angular rates of rotors, assuming that the Euler angles are minimal. After that, a many-objective optimization problem involving 20 design parameters and ten objective functions is formulated and solved by HypE (Hypervolume estimation algorithm), one of the widely used many-objective optimization algorithms approaches. Both stability and performance constraints are imposed on the optimization problem. The optimization results in terms of Pareto sets and fronts are obtained and show that some of the design objectives are competing. That is, when one objective goes down, the other goes up. Also, Numerical simulations conducted on the nonlinear UAV model show that the proposed optimization method is quite effective.

Keywords: optimal control, many-objective optimization, sliding mode control, linear control, cascade controllers, UAV, drones

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Authors: Anders S. Kristensen, Dewan Ahsan, Saqib Mehmood, Shakeel Ahmed

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Traffic accidents are a result of the convergence of hazards, malfunctioning of vehicles and human negligence that have adverse economic and health impacts and effects. Unfortunately, avoiding them completely is very difficult, but with quick response to rescue and first aid, the mortality rate of inflicted persons can be reduced significantly. Smart and innovative technologies can play a pivotal role to respond faster to traffic crash emergencies comparing conventional means of transportation. For instance, Rescue Emergency Drone (RED) can provide faster and real-time crash site risk assessment to emergency medical services, thereby helping them to quickly and accurately assess a situation, dispatch the right equipment and assist bystanders to treat inflicted person properly. To conduct a research in this regard, the case of a traffic roundabout that is prone to frequent traffic accidents on the outskirts of Esbjerg, a town located on western coast of Denmark is hypothetically considered. Along with manual calculations, Emergency Disaster Management Simulation (EDMSIM) has been used to verify the response time of RED from a fire station of the town to the presumed crash site. The results of the study demonstrate the robustness of RED into emergency services to help save lives. 

Keywords: automated external defibrillator, medical emergency, response time, unmanned aerial system

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Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Luca Garbarino, Urbano Tancredi, Domenico Accardo, Michele Grassi, Giancarmine Fasano, Anna Elena Tirri

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The development of guidance, navigation and control algorithms and avionic procedures requires the disposability of suitable analysis and verification tools, such as simulation environments, which support the design process and allow detecting potential problems prior to the flight test, in order to make new technologies available at reduced cost, time and risk. This paper presents a simulation environment for avionic software development and qualification, especially aimed at equipment for general aviation aircrafts and unmanned aerial systems. The simulation environment includes models for short and medium-range radio-navigation aids, flight assistance systems, and ground control stations. All the software modules are able to simulate the modeled systems both in fast-time and real-time tests, and were implemented following component oriented modeling techniques and requirement based approach. The paper describes the specific models features, the architectures of the implemented software systems and its validation process. Performed validation tests highlighted the capability of the simulation environment to guarantee in real-time the required functionalities and performance of the simulated avionics systems, as well as to reproduce the interaction between these systems, thus permitting a realistic and reliable simulation of a complete mission scenario.

Keywords: ADS-B, avionics, NAVAIDs, real-time simulation, TCAS, UAS ground control station

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Authors: Chiraz Ben Jabeur, Hassene Seddik

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In this paper, a full approach of modeling and control of a four-rotor unmanned air vehicle (UAV), known as quad-rotor aircraft, is presented. In fact, a PD and a PD optimized Neural Networks Approaches (PD-NN) are developed to be applied to control a quad-rotor. The goal of this work is to concept a smart self-tuning PD controller based on neural networks able to supervise the quad-rotor for an optimized behavior while tracking the desired trajectory. Many challenges could arise if the quad-rotor is navigating in hostile environments presenting irregular disturbances in the form of wind added to the model on each axis. Thus, the quad-rotor is subject to three-dimensional unknown static/varying wind disturbances. The quad-rotor has to quickly perform tasks while ensuring stability and accuracy and must behave rapidly with regard to decision-making facing disturbances. This technique offers some advantages over conventional control methods such as PD controller. Simulation results are obtained with the use of Matlab/Simulink environment and are founded on a comparative study between PD and PD-NN controllers based on wind disturbances. These later are applied with several degrees of strength to test the quad-rotor behavior. These simulation results are satisfactory and have demonstrated the effectiveness of the proposed PD-NN approach. In fact, this controller has relatively smaller errors than the PD controller and has a better capability to reject disturbances. In addition, it has proven to be highly robust and efficient, facing turbulences in the form of wind disturbances.

Keywords: hostile environment, PD and PD-NN controllers, quad-rotor control, robustness against disturbance

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Authors: Vatasta Koul, Vaibhav Sharma, Ayush Gupta, Rajesh Yadav

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Exploratory missions to Mars and Titan have increased recently with various endeavors to find an alternate home to humankind. The use of surface rovers has its limitations due to rugged and uneven surfaces of these planetary bodies. The use of aerial robots requires the complete aerodynamic characterization of these vehicles in the atmospheric conditions of these planetary bodies. The dynamic stall phenomenon is extremely important for rotary wings performance under low Reynolds number that can be encountered in Martian and Titan’s atmosphere. The current research focuses on the aerodynamic characterization and exploration of the dynamic stall phenomenon of two different airfoils viz. E387 and Selig-Donovan7003 in Martian and Titan’s atmosphere at low Reynolds numbers of 10000 and 50000. The two-dimensional numerical simulations are conducted using commercially available finite volume solver with multi-species non-reacting mixture of gases as the working fluid. The k-epsilon (k-ε) turbulence model is used to capture the unsteady flow separation and the effect of turbulence. The dynamic characteristics are studied at a fixed different constant rotational extreme of angles of attack. This study of airfoils at different low Reynolds number and atmospheric conditions on Mars and Titan will be resulting in defining the aerodynamic characteristics of these airfoils for unmanned aerial missions for outer space exploration.

Keywords: aerodynamics, dynamic stall, E387, SD7003

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Authors: Idit Avrahami, Alex Schechter, Lev Zakhvatkin

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This research focuses on developing a compact and light Hydrogen Generator (HG), coupled with fuel cells (FC) to provide a High-Energy-Density Power-Pack (HEDPP) solution, which is 10 times Li-Ion batteries. The HEDPP is designed for portable & off-grid power applications such as Drones, UAVs, stationary off-grid power sources, unmanned marine vehicles, and more. Hydrogen gas provided by this device is delivered in the safest way as a chemical powder at room temperature and ambient pressure is activated only when the power is on. Hydrogen generation is based on a stabilized chemical reaction of Sodium Borohydride (SBH) and water. The proposed solution enables a ‘No Storage’ Hydrogen-based Power Pack. Hydrogen is produced and consumed on-the-spot, during operation; therefore, there’s no need for high-pressure hydrogen tanks, which are large, heavy, and unsafe. In addition to its high energy density, ease of use, and safety, the presented power pack has a significant advantage of versatility and deployment in numerous applications and scales. This patented HG was demonstrated using several prototypes in our lab and was proved to be feasible and highly efficient for several applications. For example, in applications where water is available (such as marine vehicles, water and sewage infrastructure, and stationary applications), the Energy Density of the suggested power pack may reach 2700-3000 Wh/kg, which is again more than 10 times higher than conventional lithium-ion batteries. In other applications (e.g., UAV or small vehicles) the energy density may exceed 1000 Wh/kg.

Keywords: hydrogen energy, sodium borohydride, fixed-wing UAV, energy pack

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Authors: Maxime Alex Junior Kuitche, Ruxandra Mihaela Botez, Jean-Chirstophe Maunand

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The evolution of aircraft is closely linked to the study and improvement of propulsion systems. Determining the propulsion performance is a real challenge in aircraft modeling and design. In addition to theoretical methodologies, experimental procedures are used to obtain a good estimation of the propulsion performances. For piston-propeller propulsion, the propeller needs several experimental tests which could be extremely demanding in terms of time and money. This paper presents a new procedure to estimate the performance of a propeller from a numerical approach using computational fluid dynamic analysis. The propeller was initially scanned, and then, its 3D model was represented using CATIA. A structured meshing and Shear Stress Transition k-ω turbulence model were applied to describe accurately the flow pattern around the propeller. Thus, the Partial Differential Equations were solved using ANSYS FLUENT software. The method was applied on the UAS-S45’s propeller designed and manufactured by Hydra Technologies in Mexico. An extensive investigation was performed for several flight conditions in terms of altitudes and airspeeds with the aim to determine thrust coefficients, power coefficients and efficiency of the propeller. The Computational Fluid Dynamics results were compared with experimental data acquired from wind tunnel tests performed at the LARCASE Price-Paidoussis wind tunnel. The results of this comparison have demonstrated that our approach was highly accurate.

Keywords: CFD analysis, propeller performance, unmanned aerial system propeller, UAS-S45

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Authors: Jin Fan, M. Ala Saadeghvaziri

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Unmanned aerial vehicles (UAVs), also referred to as drones, equipped with various kinds of advanced detecting or surveying systems, are effective and low-cost in data acquisition, data delivery and sharing, which can benefit the building of infrastructures. This paper will give an overview of applications of drones in planning, designing, construction and maintenance of infrastructures. The drone platform, detecting and surveying systems, and post-data processing systems will be introduced, followed by cases with details of the applications. Challenges from different aspects will be addressed. Opportunities of drones in infrastructure include but not limited to the following. Firstly, UAVs equipped with high definition cameras or other detecting equipment are capable of inspecting the hard to reach infrastructure assets. Secondly, UAVs can be used as effective tools to survey and map the landscape to collect necessary information before infrastructure construction. Furthermore, an UAV or multi-UVAs are useful in construction management. UVAs can also be used in collecting roads and building information by taking high-resolution photos for future infrastructure planning. UAVs can be used to provide reliable and dynamic traffic information, which is potentially helpful in building smart cities. The main challenges are: limited flight time, the robustness of signal, post data analyze, multi-drone collaboration, weather condition, distractions to the traffic caused by drones. This paper aims to help owners, designers, engineers and architects to improve the building process of infrastructures for higher efficiency and better performance.

Keywords: bridge, construction, drones, infrastructure, information

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Authors: Johnson Okoduwa Imumbhon, Mohammad Didarul Alam, Yiding Cao

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Structural analyses are commonly employed to test the integrity of aircraft component systems in the design stage to demonstrate the capability of the structural components to withstand what it was designed for, as well as to predict potential failure of the components. The analyses are also essential for weight minimization and selecting the most resilient materials that will provide optimal outcomes. This research focuses on testing the structural nature of a high-lift low Reynolds number airfoil profile design, the Selig S1223, under certain loading conditions for a drone model application. The wing (ribs, spars, and skin) of the drone model was made of carbon fiber-reinforced polymer and designed in SolidWorks, while the finite element analysis was carried out in ANSYS mechanical in conjunction with the lift and drag forces that were derived from the aerodynamic airfoil analysis. Additionally, modal analysis was performed to calculate the natural frequencies and the mode shapes of the wing structure. The structural strain and stress determined the minimal deformations under the wing loading conditions, and the modal analysis showed the prominent modes that were excited by the given forces. The research findings from the structural analysis of the S1223 high-lift airfoil indicated that it is applicable for use in an unmanned aerial vehicle as well as a novel reciprocating-airfoil-driven vertical take-off and landing (VTOL) drone model.

Keywords: CFRP, finite element analysis, high-lift, S1223, strain, stress, VTOL

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Authors: Catalina Albornoz, Giacomo Barbieri

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Crop monitoring has shown to reduce vulnerability to spreading plagues and pathologies in crops. Remote sensing with Unmanned Aerial Vehicles (UAVs) has made crop monitoring more precise, cost-efficient and accessible. Nowadays, remote monitoring involves calculating maps of vegetation indices by using different software that takes either Truecolor (RGB) or multispectral images as an input. These maps are then used to segment the crop into management zones. Finally, knowing the spectral signature of a crop (the reflected radiation as a function of wavelength) can be used as an input for decision-making and crop characterization. The calculation of vegetation indices using software such as Pix4D has high precision for monoculture plantations. However, this paper shows that using this software on mixed crops may lead to errors resulting in an incorrect segmentation of the field. Within this work, authors propose to filter all the elements different from the main crop before the calculation of vegetation indices and the spectral signature. A filter based on the Sobel method for border detection is used for filtering a coffee crop. Results show that segmentation into management zones changes with respect to the traditional situation in which a filter is not applied. In particular, it is shown how the values of the spectral signature change in up to 17% per spectral band. Future work will quantify the benefits of filtering through the comparison between in situ measurements and the calculated vegetation indices obtained through remote sensing.

Keywords: coffee, filtering, mixed crop, precision agriculture, remote sensing, spectral signature

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Authors: Yildiray Korkmaz, Mehmet Aksoy

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In today's operations, countries want to reach their aims in the shortest way due to economical, political and humanitarian aspects. The most effective way of achieving this goal is to be able to penetrate strategic targets. Strategic targets are generally located deep inside of the countries and are defended by modern and efficient surface to air missiles (SAM) platforms which are operated as integrated with Intelligence, Surveillance and Reconnaissance (ISR) systems. On the other hand, these high valued targets are buried deep underground and hardened with strong materials against attacks. Therefore, to penetrate these targets requires very detailed intelligence. This intelligence process should include a wide range that is from weaponry to threat assessment. Accordingly, the framework of the attack package will be determined. This mission package has to execute missions in a high threat environment. The way to minimize the risk which depends on loss of life is to use packages which are formed by UAVs. However, some limitations arising from the characteristics of UAVs restricts the performance of the mission package consisted of UAVs. So, the mission package should be formed with UAVs under the leadership of a fifth generation manned aircraft. Thus, we can minimize the limitations, easily penetrate in the deep inside of the enemy territory with minimum risk, make a decision according to ever-changing conditions and finally destroy the strategic targets. In this article, the strengthens and weakness aspects of UAVs are examined by SWOT analysis. And also, it revealed features of a mission package and presented as an example what kind of a mission package we should form in order to get marginal benefit and penetrate into strategic targets with the development of autonomous mission execution capability in the near future.

Keywords: UAV, autonomy, mission package, strategic attack, mission planning

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Authors: Lovesh Goyal, Pushkar Dave, Prajyot Jadhav, GonnaYaswanth, Sakshi Giri, Sahil Dharme, Rushika Joshi, Rishabh Verma, Shital Chiddarwar

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With the rising need for human-robot interaction, researchers have proposed and tested multiple models with varying degrees of success. A few of these models performed on aerial platforms are commonly known as Tethered Aerial Systems. These aerial vehicles may be powered continuously by a tether cable, which addresses the predicament of the short battery life of quadcopters. This system finds applications to minimize humanitarian efforts for industrial, medical, agricultural, and service uses. However, a significant challenge in employing such systems is that it necessities attaining smooth and secure robot-human interaction while ensuring that the forces from the tether remain within the standard comfortable range for the humans. To tackle this problem, a hybrid control method that could switch between two control techniques: constant control input and the steady-state solution, is implemented. The constant control approach is implemented when a person is far from the target location, and error is thought to be eventually constant. The controller switches to the steady-state approach when the person reaches within a specific range of the goal position. Both strategies take into account human velocity feedback. This hybrid technique enhances the outcomes by assisting the person to reach the desired location while decreasing the human's unwanted disturbance throughout the process, thereby keeping the interaction between the robot and the subject smooth.

Keywords: unmanned aerial vehicle, tethered system, physical human-robot interaction, hybrid control

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Authors: Yongqin Zhang, John Lett

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Geospatial technologies have been increasingly used in agriculture for various applications and purposes in recent years. Unmanned aerial vehicles (drones) fit the needs of farmers in farming operations, from field spraying to grow cycles and crop health. In this research, we conducted a practical research project that used drone technology to design and map optimal locations and layouts of irrigation systems for agriculture farms. We flew a DJI Mavic 2 Pro drone to acquire aerial remote sensing images over two agriculture fields in Forest, Mississippi, in 2022. Flight plans were first designed to capture multiple high-resolution images via a 20-megapixel RGB camera mounted on the drone over the agriculture fields. The Drone Deploy web application was then utilized to develop flight plans and subsequent image processing and measurements. The images were orthorectified and processed to estimate the area of the area and measure the locations of the water line and sprinkle heads. Field measurements were conducted to measure the ground targets and validate the aerial measurements. Geospatial analysis and photogrammetric measurements were performed for the study area to determine optimal layout and quantitative estimates for irrigation systems. We created maps and tabular estimates to demonstrate the locations, spacing, amount, and layout of sprinkler heads and water lines to cover the agricultural fields. This research project provides scientific guidance to Mississippi farmers for a precision agricultural irrigation practice.

Keywords: drone images, agriculture, irrigation, geospatial analysis, photogrammetric measurements

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Authors: Yong Eun Yoon, Eric N. Johnson, Liling Ren

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Multirotor is one of the most popular types of small unmanned aircraft systems and has already been used in many areas including transport, military, surveillance, and leisure. Together with its popularity, the needs for proper flight control is growing because in most applications it is required to conduct its missions autonomously, which is in many aspects based on autonomous flight control. There have been many studies about the flight control for multirotor, but there is still room for enhancements in terms of performance and efficiency. This paper presents an autonomous flight control method for multirotor based on alternative input output linearization coupled with nested saturations. With alternative choice of the output of the multirotor flight control system, we can reduce computational cost regarding Lie algebra, and the linearized system can be stabilized with the introduction of nested saturations with real poles of our own design. Stabilization of internal dynamics is also based on the nested saturations and accompanies the determination of part of desired states. In particular, outer control loops involving state variables which originally are not included in the output of the flight control system is naturally rendered through this internal dynamics stabilization. We can also observe that desired tilting angles are determined by error dynamics from outer loops. Simulation results show that in any tracking situations multirotor stabilizes itself with small time constants, preceded by tuning process for control parameters with relatively low degree of complexity. Future study includes control of piecewise linear behavior of multirotor with actuator saturations, and the optimal determination of desired states while tracking multiple waypoints.

Keywords: automatic flight control, input output linearization, multirotor, nested saturations

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Authors: Luiz G. Véras, Felipe L. Medeiros, Lamartine F. Guimarães

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This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals.

Keywords: path planning, path smoothing, Pythagorean hodograph curve, RRT*-Smart

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Authors: Ya-Li Tsai

Abstract:

Nitrogen is a vital element crucial for crop growth, significantly influencing crop yield. In rice cultivation, farmers often apply substantial nitrogen fertilizer to maximize yields. However, excessive nitrogen application increases the risk of lodging and pest infestation, leading to yield losses. Additionally, conventional flooded irrigation methods consume significant water resources, necessitating precise agricultural and intelligent water management systems. In this study, it leveraged physiological data and field images captured by unmanned aerial vehicles, considering fertilizer treatment and irrigation as key factors. Statistical models incorporating rice physiological data, yield, and vegetation indices from image data were developed. Missing physiological data were addressed using multiple imputation and regression methods, and regression models were established using principal component analysis and stepwise regression. Target nitrogen accumulation at key growth stages was identified to optimize fertilizer application, with the difference between actual and target nitrogen accumulation guiding recommendations for ear dressing dosage. Field experiments conducted in 2022 validated the recommended ear dressing dosage, demonstrating no significant difference in final yield compared to traditional fertilizer levels under alternate wetting and drying irrigation. These findings highlight the efficacy of applying recommended dosages based on fertilizer decision models, offering the potential for reduced fertilizer use while maintaining yield in rice cultivation.

Keywords: intelligent fertilizer management, nitrogen top and ear dressing fertilizer, rice, yield optimization

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Authors: Gary Pattemore, Michael Edgar, Andrew Job, Marina Auad, Kathryn Job

Abstract:

As critical commodities become more scarce, significant time and resources have been used to better understand complicated ore bodies and extract their full potential. These challenging ore bodies provide several pain points for geologists and engineers to overcome, poor handling of these issues flows downs stream to the processing plant affecting throughput rates and recovery. Many open cut mines utilise blast hole drilling to extract additional information to feed back into the modelling process. This method requires samples to be collected during or after blast hole drilling. Samples are then sent for assay with turnaround times varying from 1 to 12 days. This method is time consuming, costly, requires human exposure on the bench and collects elemental data only. To address this challenge, research has been undertaken to utilise hyperspectral imaging across a broad spectrum to scan samples, collars or take down hole measurements for minerals and moisture content and grade abundances. Automation of this process using unmanned vehicles and on-board processing reduces human in pit exposure to ensure ongoing safety. On-board processing allows data to be integrated into modelling workflows with immediacy. The preliminary results demonstrate numerous direct and indirect benefits from this new technology, including rapid and accurate grade estimates, moisture content and mineralogy. These benefits allow for faster geo modelling updates, better informed mine scheduling and improved downstream blending and processing practices. The paper presents recommendations for implementation of the technology in open cut mining environments.

Keywords: grade control, hyperspectral scanning, artificial intelligence, autonomous mining, machine learning

Procedia PDF Downloads 79

Authors: Yang Ye, Hongfei Qiu, Yaqi Li

Abstract:

The planning and construction of traditional cities are oriented by cars, which leads to the problems of insufficient urban public space, fragmentation, and low utilization efficiency. With the development of driverless technology, the urban structure will change from the traditional single-core grid structure to the multi-core model. In terms of traffic organization, with the release of land for traffic facilities, public space will become more continuous and integrated with traffic space. In the context of driverless technology, urban public reconstruction is characterized by modularization and high efficiency, and its planning and layout features accord with points (service facilities), lines (smart lines), surfaces (activity centers). The public space of driverless urban roads will provide diversified urban public facilities and services. The intensive urban layout makes the commercial public space realize the functions of central activities and style display, respectively, in the interior (building atrium) and the exterior (building periphery). In addition to recreation function, urban green space can also utilize underground parking space to realize efficient dispatching of shared cars. The roads inside the residential community will be integrated into the urban landscape, providing conditions for the community public activity space with changing time sequence and improving the efficiency of space utilization. The intervention of driverless technology will change the thinking of traditional urban construction and turn it into a human-oriented one. As a result, urban public space will be richer, more connected, more efficient, and the urban space justice will be optimized. By summarizing the frontier research, this paper discusses the impact of unmanned driving on cities, especially urban public space, which is beneficial for landscape architects to cope with the future development and changes of the industry and provides a reference for the related research and practice.

Keywords: driverless, urban public space, construction strategy, urban design

Procedia PDF Downloads 87

Authors: Daniele Calvi, Loris Franchi, Sabrina Corpino

Abstract:

Thanks to the latest Mars mission, the planetary exploration has made enormous strides over the past ten years increasing the interest of the scientific community and beyond. These missions aim to fulfill many complex operations which are of paramount importance to mission success. Among these, a special mention goes to the Entry, Descent and Landing (EDL) functions which require a dedicated system to overcome all the obstacles of these critical phases. The general objective of the system is to safely bring the spacecraft from orbital conditions to rest on the planet surface, following the designed mission profile. For this reason, this work aims to develop a simulation tool integrating the re-entry trajectory algorithm in order to support the EDL design during the preliminary phase of the mission. This tool was used on a reference unmanned mission, whose objective is finding bio-evidence and bio-hazards on Martian (sub)surface in order to support the future manned mission. Regarding the concept of operations (CONOPS) of the mission, it concerns the use of Space Penetrator Systems (SPS) that will descend on Mars surface following a ballistic fall and will penetrate the ground after the impact with the surface (around 50 and 300 cm of depth). Each SPS shall contain all the instrumentation required to sample and make the required analyses. Respecting the low-cost and low-mass requirements, as result of the tool, an Entry Descent and Impact (EDI) system based on inflatable structure has been designed. Hence, a solution could be the one chosen by Finnish Meteorological Institute in the Mars Met-Net mission, using an inflatable Thermal Protection System (TPS) called Inflatable Braking Unit (IBU) and an additional inflatable decelerator. Consequently, there are three configurations during the EDI: at altitude of 125 km the IBU is inflated at speed 5.5 km/s; at altitude of 16 km the IBU is jettisoned and an Additional Inflatable Braking Unit (AIBU) is inflated; Lastly at about 13 km, the SPS is ejected from AIBU and it impacts on the Martian surface. Since all parameters are evaluated, it is possible to confirm that the chosen EDI system and strategy verify the requirements of the mission.

Keywords: EDL, Mars, mission, SPS, TPS

Procedia PDF Downloads 134

Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

Abstract:

In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

Procedia PDF Downloads 183

Authors: Yichin Chen

Abstract:

Taiwan is an island characterized by an active tectonics and high erosion rates. Monitoring the dynamic landscape of Taiwan is an important issue for disaster mitigation, geomorphological research, and watershed management. Long-term and high spatiotemporal landform data is essential for quantifying and simulating the geomorphological processes and developing warning systems. Recently, the advances in unmanned aerial vehicle (UAV) and computational photogrammetry technology have provided an effective way to rebuild and monitor the topography changes in high spatio-temporal resolutions. This study rebuilds the 30-years landform change in the Aiyuzi watershed in 1986-2017 by using the aerial photogrammetry-based techniques. The Aiyuzi watershed, located in central Taiwan and has an area of 3.99 Km², is famous for its frequent landslide and debris flow disasters. This study took the aerial photos by using UAV and collected multi-temporal historical, stereo photographs, taken by the Aerial Survey Office of Taiwan’s Forestry Bureau. To rebuild the orthoimages and digital surface models (DSMs), Pix4DMapper, a photogrammetry software, was used. Furthermore, to control model accuracy, a set of ground control points was surveyed by using eGPS. The results show that the generated DSMs have the ground sampling distance (GSD) of ~10 cm and ~0.3 cm from the UAV’s and historical photographs, respectively, and vertical error of ~1 m. By comparing the DSMs, there are many deep-seated landslides (with depth over 20 m) occurred on the upstream in the Aiyuzi watershed. Even though a large amount of sediment is delivered from the landslides, the steep main channel has sufficient capacity to transport sediment from the channel and to erode the river bed to ~20 m in depth. Most sediments are transported to the outlet of watershed and deposits on the downstream channel. This case study shows that UAV and photogrammetry technology are useful for topography change monitoring effectively.

Keywords: aerial photogrammetry, landslide, landform change, Taiwan

Procedia PDF Downloads 128